An Improved Hybrid Particle Swarm Optimization and Tabu Search Algorithm for Expansion Planning of Large Dimension Electric Distribution Network

Ali Ahmadian, Ali Elkamel and Abdelkader Mazouz
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Ali Ahmadian: College of Engineering, University of Waterloo, Waterloo, ON N2J 0A1, Canada
Ali Elkamel: College of Engineering, University of Waterloo, Waterloo, ON N2J 0A1, Canada
Abdelkader Mazouz: College of Business Administration, Al Ain University of Science and Technology, Al Ain 64141, UAE

Energies, 2019, vol. 12, issue 16, 1-14

Abstract: Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing the total cost of the objective function with technical constraints make it a combinatorial problem which should be solved by powerful optimization algorithms. In this paper, a new improved hybrid Tabu search/particle swarm optimization algorithm is proposed to optimize the electric expansion planning. The proposed method is analyzed both mathematically and experimentally and it is applied to three different electric distribution networks as case studies. Numerical results and comparisons are presented and show the efficiency of the proposed algorithm. As a result, the proposed algorithm is more powerful than the other algorithms, especially in larger dimension networks.

Keywords: electric distribution network planning; optimization; particle swarm optimization; tabu search (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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